Olympics

Olympic Rings

Intro

The Olympics are a worldwide celebration of the best athletes in the world that promotes peace and unity. There are no honors greater for athletes than winning a gold medal for their country. This incredible achievement may be influenced by obvious variables such as physical traits of the athletes, the type of olympics (summer or winter), or variables that one would not think are immediately related to sports. We suspect that factors such as a country’s total GDP and Population. We explore if these factors influence the number of medals won in the Olympics in this blog. Our aim is to deepen our understanding of what factors influence a country’s success in the games and spread the information in hopes that there may be a solution to even the playing field.

USA Medal Exploration

The above medal time graph demonstrates the number of medals that the United States won each year that the Olympics were held. This allows us to see how the United States has performed at the Olympic stage. The graph has very sharp curves up and down which represent the medal differences between the summer and winter olympics. The USA tends to win more medals in the summer Olympics than the Winter olympics.

2016 Olympic Data Analysis

The graph above depicts the relationship between a country’s GDP and its medal count at the 2016 Olympic Games. It is evident that a significant cluster of countries with low GDP and low medal count exists, indicating that many small countries were not large medal winners. The data suggests that only two countries, the United States and China, managed to surpass the 50 medal count threshold, which correlates with their relatively high GDP. Additionally, the size of the points on the graph corresponds to a country’s population, but it is clear that population is not as predictive of medal count as GDP. This is evident as there are large and small points at both ends of the y-axis (medal count).

GDP and Population Country Maps (2010)

GDP

This map displays Total GDP in 2010 for countries around the world. Lighter shades indicate a lower total GDP, while darker shades represent a higher GDP. Countries such as China, The United States of America, and Japan are among the countries with the highest Total GDP. Users can hover over the country of their choice to identify the country’s name and its Total GDP.

Population

This map displays populations for countries around the world in 2010. Lighter shades indicate a relatively low population, while dark shades indicate a relatively high population. China and India are among the countries with the highest total population by a considerable margin. Users can hover over the country of their choice to identify the country’s name and its population. ## {-}

Population and Medals won in 2016 Olympics

This map displays the medals won in the 2016 Olympics versus the population of countries around the world in 2016. Lighter shades indicate a relatively low number of medals when compared to the population, while dark shades indicate a high number of medals when compared to the population. Grey represents the countries who did not win medals during the 2016 Olympics. Georgia, Azerbaijan, and Denmark are among the countries with the highest number of medals in context of their populations. Countries with high GDPs or populations such as the United States, China, Japan, and Brazil all won medals during the Olympics. Users can hover over the countries to view the country’s name and Medals won in comparison to their population. The maps were created using ggplot in R.

Athlete Medal Analysis

Height

cluster	min	Q1	median	Q3	max	mean	sd	n
1	136	163	167	170	179	166.01	6.08	9903
2	164	187	190	195	223	191.33	6.66	6679
3	162	176	180	183	203	179.39	4.73	13599

Weight

cluster	min	Q1	median	Q3	max	mean	sd	n
1	28	55	59	64	90	58.80	6.84	9903
2	70	87	92	98	182	94.05	11.06	6679
3	54	70	75	79	104	74.68	6.29	13599

This bar graph pulls from a dataset containing every Olympic medal winner in the competition’s history (since data collection began). As you can see, the data is clustered. I clustered the data by height and weight, and measured the total medal count for each cluster, separated by the type of medal.

The goal here is to observe how height and weight may hold an impact on whether or not an athlete will be successful in the olympics. Evidently, the 1st and 3rd clusters observed the most medaling. From this, we can conclude that the highest third of athletes by height and weight are more likely to medal than other shorter and lighter athletes. In a similar vein, the lowest third of athletes by height and weight are more likely to medal than the middle third.

Similarly, we can observe individual types of medals across these three clusters. The same trend I described before is generally true for each type of medal, with the heaviest and tallest athletes winning the most gold, silver, and bronze medals. Though, the difference between the first two clusters is much less major.

Conclusion

Evidently, we have chosen a quite broad discussion topic. While we are interested in looking at country specific trends relating to the olympics, such as our first graph where we observe medal count for just the United States, we are also dive into quite universal trends amongst athletes throughout the world, such as our graphs on GDP and height and weight.

We take this broad approach so as to identify multiple factors which impact a nation or individual athlete’s ability to be successful at the Olympics. Our final conclusions given these visualizations is prone to change come final submission. At this very moment, it seems clear that, at the national level, economic strength plays a major role in the success of a nation at the Olympics. There are many reasons why this may be true, however, it is clear that the more money a nation has, the more money they can pour into resources for building up incredible athletes. On the other hand, however, these economic factors have very little impact on the quite natural aspects of an athlete’s physical traits. At the individual level, it may be true that heavier and taller athletes are the most succesfull, closely followed by the shortest and lightest.

It would be great to identify which of these factors holds a more marginal impact on success, however, at this very moment it is not clear what the most important factor is. We can make an effort to distinguish this before final submission. At the very least, however, it is clear that there are a number of factors which potentially impact success at the Olympics.

References

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